Instructions to use uclanlp/plbart-single_task-all-summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uclanlp/plbart-single_task-all-summarization with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("uclanlp/plbart-single_task-all-summarization") model = AutoModelForSeq2SeqLM.from_pretrained("uclanlp/plbart-single_task-all-summarization") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d613df5fba1c0ccf0773980ce97618ab9b0123042c7f9abb8875de097f0b918
- Size of remote file:
- 557 MB
- SHA256:
- 2bd50722fa00cceeb5af1eef8a3d77e37614a06a8ea3ec74de10f0f5a283e420
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.